Cyber Security

4 Key IT Trends for CIOs in 2017

The new year comes with new resolutions for CIOs. Innovation is the key in technology, but CIOs should aim for something that drives their companies and leaves other competitors behind. Mark Campbell at the Enterprisers Project points out four hot IT trends that CIOs should focus on in this year:

  1. Enhancing cybersecurity
  2. Better data visualization
  3. Using containers to improve other IT layers
  4. Adopting one single storage system to back up data

Keep Up with the Trends

Cybersecurity has never been outdated with the increase in damaging hacks and breaches. People are getting better every day with IT, and unfortunately, not all of them are good people. In order to protect confidential information of users including partners, customers, and even non-human apps, smart bots will be a great help in improving identity access management and multifactor identity analytics.

Using containers and a single storage system for data backup is the next step in proliferating businesses. If you are a savvy CIO, you will realize that it is unwise to spend tons of money on multiple storage systems to duplicate so much useless data. A single storage system and containers in smoothing orchestration would not impact the operations but prove better to manage data.

Campbell also touches on the need for better data visualization in order to appeal to non-technical audiences:

Forward-looking, predictive analytics will also become more crucial to maintain a strong business edge. Prior-year and year-to-date results will be replaced by platforms that can predict the future, or at least give management the statistical probability for future outcomes. In this way, for instance, CIOs can set aside enough lead time to order new infrastructure long before any critical capacity threshold is threatened.

Another data management trend involves a shifting approach to data warehousing. For years, IT departments have pooled information from across their companies into a single data lake or data warehouse. Such efforts involved lots of extra work to cleanse and normalize the data.

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